Documents & Reports

Setting targets in health, nutrition and population projects (English)

Abstract

This note discusses different ways for setting targets for indicators commonly used in World Bank Health, Nutrition and Population (HNP) projects. It shows how targets can be set, using information about historical progress, for a selection of HNP indicators... See More +This note discusses different ways for setting targets for indicators commonly used in World Bank Health, Nutrition and Population (HNP) projects. It shows how targets can be set, using information about historical progress, for a selection of HNP indicators. Targets are defined as explicit commitments to achieve a result within a defined time period, as measured by a quantitative or qualitative change in an indicator. The selection of indicators, which are clearly defined and useful for measuring progress, is an important part of the process. The note includes a discussion of general considerations for selecting indicators for which targets are to be set. The note also briefly reviews different methods that have been used to set targets, including benchmarking, time-series analysis, and projections, and multivariate regression analysis. In some cases, a mixed-method approach that combines elements from several different procedures is a practical way to set targets. A checklist for target setting including considerations about the availability of baselines, factors affecting the potential for achieving targets, and the need for data verification is also included. The note is followed by annexes that show how targets are derived through an analysis of changes in nine key HNP indicators. The result of the analysis shows that, in general, annual improvements have been fairly modest for the HNP indicators included here. This finding underlines the need for realism in setting targets, despite the expectation that a Bank project will produce substantial improvements. A second important point is that prior year coverage rates (or outcomes) are not generally strong predictors of improvements, strengthening the argument for using multiple approaches when selecting targets.
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